Biology subjects

Filo, S.

Publications and source records attributed to Filo, S..

5 recordsLinked to original sources

bioRxiv2026

Distinct cortical networks associated with subregions of the hippocampal-entorhinal system in the first two years of human life

Episodic memory critically depends on the hippocampus and the entorhinal cortex. Despite a rapid developmental change in human episodic memory during the first two years of life, little is known about the developmental trajectory of the hippocampal-entorhinal circuitry during this critical time period. In the current study, we collected high-quality precision fMRI data from five typically developing infants over the time period between 1 and 2 years of life and examined, in great anatomical detail, the developmental profile of distinct parts of the infant hippocampal-entorhinal system and their coupling with distinct cortical networks. We show that already at around 1 year of age, subdivisions of the canonical default network (DN) are fully dissociated at the neocortex and are differently associated with the hippocampal-entorhinal system, with tentatively differential developmental trajectories. While the DN-A, associated with episodic simulation, coupled with the anterior hippocampus and the medial part of the entorhinal cortex, the DN-B, associated with social cognition, showed significantly weaker connectivity with the hippocampal-entorhinal system. Furthermore, the parietal memory network coupled with the posterior hippocampus and the lateral part of the entorhinal cortex. Exploratory longitudinal results suggest that associations of the DN-B with the hippocampus and the entorhinal cortex increase towards the end of the second postnatal year, and the associations of the parietal memory network become more topographically restricted to the posterior hippocampus. These networks and their differential maturation may provide the basis for important developments in episodic memory and social cognition in the second postnatal year and suggest that potentially unique properties of human hippocampal-entorhinal circuitry may emerge latest in development.

neuroscience↗

bioRxiv2025

Loss of Brain Structural qMRI Signatures in Aging

The human brain undergoes significant changes during aging, affecting its macrostructure and microstructure features and impacting its functionality. These aging-related changes are oftentimes linked to different neurodegenerative diseases. Previous studies using MRI and molecular analyses have proposed that aging in each individual brain leads to increased similarity between different brain regions, whereas on the population level, they show greater variability. We investigated these hypotheses using multi-parametric, microstructural, quantitative MRI (qMRI) approaches. Using seven qMRI parametric methods in data from young and older adults, we created unique microstructural signatures of 128 brain regions. Our results supported both hypotheses: First, that inter-regional microstructural similarity is stronger within older individuals; and second, that the variability in microstructural signatures across individuals is also greater in older than in younger adults. Our findings provide new insights into the brains microstructural changes during aging and demonstrate the potential of using multi-parameter qMRI techniques in neuroscience research.

neuroscience↗

bioRxiv2024

A qMRI approach for mapping microscopic water populations and tissue relaxivity in the in vivo human brain.

Quantitative magnetic resonance imaging (qMRI) enables non-invasive mapping of brain tissue microstructure and is widely used for monitoring various physiological and pathological brain processes. Here, we introduce a qMRI approach for enriching the microstructural characterization of the sub-voxel environment. Inspired by pioneering magnetization transfer (MT) models, this approach employs MT saturation to differentiate between various water populations within each voxel. Our in vivo results align well with theoretical predictions and are reproducible using standard qMRI protocols. We present an array of new quantitative maps, highlighting different aspects of the tissues water. Furthermore, by manipulating the effective water content and relaxation rate with MT, we approximate within the voxel the tissue relaxivity. This property reflects the dependency of R1 on the macromolecular tissue volume (MTV) and is associated with the lipid and macromolecular composition of the brain. Our approach also enables biophysically-informed modulation of the R1 contrast, resulting in a set of unique cortical profiles. Finally, we demonstrate the effectiveness of our technique in imaging the common pathology of white matter hyperintensities (WMH), revealing tissue degradation and molecular alterations.

neuroscience↗

bioRxiv2022

Uncovering molecular iron compounds in the living human brain.

Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissues iron homeostasis remains a challenge. We present a novel magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/490254v2_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@17e2722org.highwire.dtl.DTLVardef@13b646aorg.highwire.dtl.DTLVardef@3d9bfeorg.highwire.dtl.DTLVardef@cc5b7d_HPS_FORMAT_FIGEXP M_FIG Non-invasive assessment of normal and impaired iron homeostasis in living human brains. C_FIG

neuroscience↗

bioRxiv2018

Modelling conduction delays in the corpus callosum using MRI-measured g-ratio

Conduction of action potentials along myelinated axons is affected by their structural features, such as the axonal g-ratio, the ratio between the inner and outer diameters of the myelin sheath surrounding the axon. The effect of g-ratio variance on conduction properties has been quantitatively evaluated using single-axon models. It has recently become possible to estimate a g-ratio weighted measurement in vivo using quantitative MRI. Nevertheless, it is still unclear whether the variance in the g-ratio in the healthy human brain leads to significant differences in conduction velocity. In this work we tested whether the g-ratio MRI measurement can be used to predict conduction delays in the corpus callosum. We present a novel framework in which the structural properties of fibers (i.e. length and g-ratio, measured using MRI), are incorporated in a biophysical model of axon conduction, to predict conduction delays of long-range white matter fibers. We applied this framework to the corpus callosum, and found conduction delay estimates that are compatible with previously estimated values of conduction delays. We account for the variance in the velocity given the axon diameter distribution in the splenium, mid-body and genu, to further compare the fibers within the corpus callosum. Conduction delays have been suggested to increase with age. Therefore, we investigated whether there are differences in the g-ratio and the fiber length between young and old adults, and whether this leads to a difference in conduction speed and delays. We found small but significant differences between the predicted delays of the two groups in the motor fibers of the corpus callosum. We also found that the motor fibers of the corpus callosum have the fastest conduction estimates. Using the axon diameter distributions, we found that the occipital fibers have the slowest estimations, while the frontal and motor fiber tracts have similar estimates. Our study provides a framework for predicting conduction latencies in vivo. The framework could have major implications for future studies of white matter diseases and large range network computations. Our results highlight the need for improving additional in vivo measurements of white matter microstructure.

neuroscience↗